<!-- This comment will put IE 6, 7 and 8 in quirks mode -->
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<title>Class Members - Functions</title>
<script type="text/javaScript" src="search/search.js"></script>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3.0.1/es5/tex-mml-chtml.js"></script>
<script src="../../mlstyle.js"></script>
<link href="../css/besser.css" rel="stylesheet" type="text/css"/>
</head>
<!-- pretty cool: each body gets an id tag which is the basename of the web page  -->
<!--              and allows for page-specific CSS. this is client-side scripted, -->
<!--              so the id will not yet show up in the served source code -->
<script type="text/javascript">
    jQuery(document).ready(function () {
        var url = jQuery(location).attr('href');
        var pname = url.substr(url.lastIndexOf("/")+1, url.lastIndexOf(".")-url.lastIndexOf("/")-1);
        jQuery('#this_url').html('<strong>' + pname + '</strong>');
        jQuery('body').attr('id', pname);
    });
</script>
<body>
    <div id="shark_old">
        <div id="wrap">
            <div id="header">
                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
                <ul id="nav">
                    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/installation.html">Installation</a>
                    </li>
		    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/tutorials/tutorials.html">Tutorials</a>
                    </li>
		    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/benchmark.html">Benchmarks</a>
                    </li>
                    <li class="active">
                        <a href="classes.html">Documentation</a>
                        <ul>
                            <li class="first"></li>
                            <li><a href="../../sphinx_pages/build/html/rest_sources/quickref/quickref.html">Quick references</a></li>
                            <li><a href="classes.html">Class list</a></li>
                            <li class="last"><a href="group__shark__globals.html">Global functions</a></li>
                        </ul>
                    </li>
                </ul>
            </div>
        </div>
    </div>
<div id="doxywrapper">
<!--
    <div id="global_doxytitle">Doxygen<br>Documentation:</div>
-->
    <div id="navrow_wrapper">
<!-- Generated by Doxygen 1.9.8 -->
</div><!-- top -->
<div class="contents">
<div class="textblock">Here is a list of all functions with links to the classes they belong to:</div>

<h3><a id="index_l" name="index_l"></a>- l -</h3><ul>
<li>label()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_box_decomp.html#aa8b9277779382ed758e61e86a22bd990">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a8cc961f63f6f3cb17ebda1b48e4ca3bc">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>LabeledData()&#160;:&#160;<a class="el" href="group__shark__globals.html#gacb49015294f7ca2d8d79e3cd90814468">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>LabelOrder()&#160;:&#160;<a class="el" href="classshark_1_1_label_order.html#afc8707eeb4e64581cfdecedcdb3fe831">shark::LabelOrder</a></li>
<li>labels()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga6328a5aa2570c01a5ac5f25076071663">shark::LabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136">shark::WeightedLabeledData&lt; InputT, LabelT &gt;</a></li>
<li>labelShape()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga7f3308a970a6f4fe96aebf23755a6430">shark::LabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="classshark_1_1_weighted_labeled_data.html#ab551802a4a3d30b09984ee7c92ca64b5">shark::WeightedLabeledData&lt; InputT, LabelT &gt;</a></li>
<li>lambda()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a7beed1a597007c62fe9e397c5e6ea6f6">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#acb8da1ec19b5869fcb6df0118d36ae9a">shark::CMSA</a>, <a class="el" href="classshark_1_1_lasso_regression.html#a424828aaade483a29aab0382ebbaceb8">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#aa9cfa27f5a150ef3a701ee208961a838">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#a0937e25d91951e5e8f10923ab5da5340">shark::LMCMA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#a69f5bc9d17bfbbe896e8925586bdbba5">shark::VDCMA</a></li>
<li>lambda1()&#160;:&#160;<a class="el" href="classshark_1_1_logistic_regression.html#a6608d0494e8d9cc32d6a1a14a9ddbd90">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>lambda2()&#160;:&#160;<a class="el" href="classshark_1_1_logistic_regression.html#ab803c9232597463aa686b02434d3a15f">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>largest()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_contribution2_d.html#a28762ad8d869ae3549fe4f63394de105">shark::HypervolumeContribution2D</a>, <a class="el" href="structshark_1_1_hypervolume_contribution3_d.html#a21b543685d2c16e733c932f8ca4f41d9">shark::HypervolumeContribution3D</a>, <a class="el" href="structshark_1_1_hypervolume_contribution.html#ad7aba98bf20f20f16135b2e2f3b5ea2b">shark::HypervolumeContribution</a>, <a class="el" href="structshark_1_1_hypervolume_contribution_m_d.html#acaab1a44fb4b791251f0fbfaa69bb55d">shark::HypervolumeContributionMD</a></li>
<li>LassoRegression()&#160;:&#160;<a class="el" href="classshark_1_1_lasso_regression.html#a6d72b15b0f10134187f75ecf51d2dde2">shark::LassoRegression&lt; InputVectorType &gt;</a></li>
<li>lastLap()&#160;:&#160;<a class="el" href="classshark_1_1_timer.html#a91e2a527ffbe3eabc7c8cf36ff742318">shark::Timer</a></li>
<li>LBFGS()&#160;:&#160;<a class="el" href="classshark_1_1_l_b_f_g_s.html#af1a1c3e07e77e4183383cd506ce121da">shark::LBFGS&lt; SearchPointType &gt;</a></li>
<li>LCTree()&#160;:&#160;<a class="el" href="classshark_1_1_l_c_tree.html#a2b66673868580ce17413f497f131e5df">shark::LCTree&lt; VectorType, CuttingAccuracy &gt;</a></li>
<li>LDA()&#160;:&#160;<a class="el" href="classshark_1_1_l_d_a.html#ae9ed3a8047ccb47a568eb7b6ec638efb">shark::LDA</a></li>
<li>learningRate()&#160;:&#160;<a class="el" href="classshark_1_1_population_based_step_size_adaptation.html#a79add20d49ef3b80a2d462859eec8f61">shark::PopulationBasedStepSizeAdaptation</a>, <a class="el" href="classshark_1_1_steepest_descent.html#aba0edaf42d57bfb853f814e362415ae5">shark::SteepestDescent&lt; SearchPointType &gt;</a></li>
<li>leastContributor()&#160;:&#160;<a class="el" href="structshark_1_1_additive_epsilon_indicator.html#a10777ba88cd77e98ba5c08cbca3335aa">shark::AdditiveEpsilonIndicator</a>, <a class="el" href="structshark_1_1_crowding_distance.html#ab70a4a4d43580f6912b616d547352e1b">shark::CrowdingDistance</a>, <a class="el" href="structshark_1_1_hypervolume_indicator.html#afb990cd72ca80aed7cd71079d39aa1ca">shark::HypervolumeIndicator</a></li>
<li>leastContributors()&#160;:&#160;<a class="el" href="structshark_1_1_additive_epsilon_indicator.html#a822ea35021309c86e3f2ce76442354b9">shark::AdditiveEpsilonIndicator</a>, <a class="el" href="structshark_1_1_crowding_distance.html#accb25d9b19ea166cc6ed1df68121ec63">shark::CrowdingDistance</a>, <a class="el" href="structshark_1_1_hypervolume_indicator.html#ae06eafa811c6d1af216ef947491516c9">shark::HypervolumeIndicator</a>, <a class="el" href="structshark_1_1_n_s_g_a3_indicator.html#ae2a8e94c8556e915e1c7e306159a432b">shark::NSGA3Indicator</a></li>
<li>left()&#160;:&#160;<a class="el" href="classshark_1_1_binary_tree.html#ae20385cf5cf85d7168db9b3fcf411c47">shark::BinaryTree&lt; InputT &gt;</a></li>
<li>lg()&#160;:&#160;<a class="el" href="classshark_1_1_pegasos.html#aaae1ce4a6bf53bb5733bf5f2f692efbb">shark::Pegasos&lt; VectorType &gt;</a></li>
<li>line()&#160;:&#160;<a class="el" href="classshark_1_1_exception.html#a95d2ea51b7cff98974705365f0603903">shark::Exception</a></li>
<li>linear()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#a73aaea4e475b7d635e48f793202716c9">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#afe5c70e6047a13481b3f3dbfbd3b7b4e">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>LinearClassifier()&#160;:&#160;<a class="el" href="classshark_1_1_linear_classifier.html#a915efe9d7464c2c5bb2ed20102caa5fb">shark::LinearClassifier&lt; VectorType &gt;</a></li>
<li>LinearCSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_linear_c_svm_trainer.html#a8677b6f19ea68f188cbb249edc895e9c">shark::LinearCSvmTrainer&lt; InputType &gt;</a></li>
<li>LinearKernel()&#160;:&#160;<a class="el" href="classshark_1_1_linear_kernel.html#a1e5f7efc56dc2f75895fea4f7ea2a779">shark::LinearKernel&lt; InputType &gt;</a></li>
<li>LinearModel()&#160;:&#160;<a class="el" href="classshark_1_1_linear_model.html#a7ab8185eb1133a27b4a483422c73d614">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a></li>
<li>LinearNoise()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method_1_1_linear_noise.html#a7c766e1314d0c921ccf2a6d2bbed76d5">shark::CrossEntropyMethod::LinearNoise</a></li>
<li>LinearRankingSelection()&#160;:&#160;<a class="el" href="structshark_1_1_linear_ranking_selection.html#a13bfbfd23561a7b6a652952e2d00ce13">shark::LinearRankingSelection&lt; Ordering &gt;</a></li>
<li>LinearRegression()&#160;:&#160;<a class="el" href="classshark_1_1_linear_regression.html#a33f1e9c741616f6cb5e64953bc721b66">shark::LinearRegression</a></li>
<li>LinearSAGTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#a160c3456f148c696d13aee3a0dcca402">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a></li>
<li>lineLength()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#ad8cae64a351bdef5e03976d1e5176072">shark::LRUCache&lt; T &gt;</a></li>
<li>lineSearch()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_line_search_optimizer.html#a81c26e0694b3b7912be4a7deaab6a496">shark::AbstractLineSearchOptimizer&lt; SearchPointType &gt;</a></li>
<li>LineSearch()&#160;:&#160;<a class="el" href="classshark_1_1_line_search.html#ab909daa31662c63dbfc3a06c59c663fd">shark::LineSearch&lt; SearchPointType &gt;</a></li>
<li>lineSearchType()&#160;:&#160;<a class="el" href="classshark_1_1_line_search.html#aa6a5189c633cdb9afa68766fbf0e450e">shark::LineSearch&lt; SearchPointType &gt;</a></li>
<li>listIndex()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#a96690c348d7b3e7b45f5efbb093da7e6">shark::LRUCache&lt; T &gt;</a></li>
<li>LMCMA()&#160;:&#160;<a class="el" href="classshark_1_1_l_m_c_m_a.html#a1f2852ce27c7333c44630c5294246c42">shark::LMCMA</a></li>
<li>load()&#160;:&#160;<a class="el" href="classshark_1_1_i_serializable.html#abdda0c5b8e065b8afbac2cba8f58e841">shark::ISerializable</a></li>
<li>LogisticRegression()&#160;:&#160;<a class="el" href="classshark_1_1_logistic_regression.html#a825243d1d1a808be12d822333c58f6fd">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>logMarginalize()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a2832d25febb06b1917b596dce09af065">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a93a04cba139d2789df22e443ea19118a">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#ada4d3177d4f9f4befe18168f9281ae47">shark::GaussianLayer</a></li>
<li>logProbability()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#ab776217f2bebdb728e4c377db40c4ec9">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a98d488be99ea2223e46ace483bbcc728">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a117e4b765db5d8b37c2446ae6451937e">shark::GaussianLayer</a></li>
<li>logUnnormalizedProbabilityHidden()&#160;:&#160;<a class="el" href="structshark_1_1_energy.html#afa5365f469f52d0682d3820fb071fa1b">shark::Energy&lt; RBM &gt;</a></li>
<li>logUnnormalizedProbabilityVisible()&#160;:&#160;<a class="el" href="structshark_1_1_energy.html#a7d21da0cfe60fabb495a5fa0d75cce51">shark::Energy&lt; RBM &gt;</a></li>
<li>LooError()&#160;:&#160;<a class="el" href="classshark_1_1_loo_error.html#abf0bc6ef63dc7648e2fc257b7c6587cb">shark::LooError&lt; ModelTypeT, LabelType &gt;</a></li>
<li>LooErrorCSvm()&#160;:&#160;<a class="el" href="classshark_1_1_loo_error_c_svm.html#a5edf0690f5406fc44ba13806e91c72b0">shark::LooErrorCSvm&lt; InputType, CacheType &gt;</a></li>
<li>lossGradientADM()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#afbc4cd9e7322908c8aaf2c60b58e27af">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lossGradientADS()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#ae477032ac112037c0f7bcf1178a60173">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lossGradientANH()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#a0562f636d27be3132daa1f9e68f1bda9">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lossGradientATM()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#a47cbf1499724ebd11c46738a06b5b10f">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lossGradientATS()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#a4dde2469b6bce8ab4bd5846c388004ea">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lossGradientRDM()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#a3685c0b79cd8ed1b8ad8f730bee3d836">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lossGradientRDS()&#160;:&#160;<a class="el" href="classshark_1_1_mc_pegasos.html#afdee49e649204c16765c03464bf97f01">shark::McPegasos&lt; VectorType &gt;</a></li>
<li>lower()&#160;:&#160;<a class="el" href="classshark_1_1_box_constraint_handler.html#a8de148cc2f808bb97a4538a0902fee5e">shark::BoxConstraintHandler&lt; Vector &gt;</a>, <a class="el" href="classshark_1_1_k_d_tree.html#aefe4d7d7a1833f518b5b3a3ad1adb520">shark::KDTree&lt; InputT &gt;</a></li>
<li>lowerBound()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a67da4539c2b2e375f2c308c190fc5b4f">shark::CMA</a></li>
<li>lowerCholeskyFactor()&#160;:&#160;<a class="el" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ac47101432c4252ea0a86ae4e622cb69a">shark::MultiVariateNormalDistributionCholesky</a></li>
<li>LowerQuantile()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_lower_quantile.html#a712a7a241400231945d95c1f02f5e74a">shark::statistics::LowerQuantile</a></li>
<li>LRUCache()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#ad2dd07a0ed9d6628dd54328e9131352b">shark::LRUCache&lt; T &gt;</a></li>
<li>LZ1()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z1.html#a4f49d50aa120d1c272eb62995aac5fcd">shark::benchmarks::LZ1</a></li>
<li>LZ2()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z2.html#af0a8146e80fb6468ce3eed39f059a7d5">shark::benchmarks::LZ2</a></li>
<li>LZ3()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z3.html#a218132b4f14accc2ce923f26cc992865">shark::benchmarks::LZ3</a></li>
<li>LZ4()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z4.html#a1e46892b10da91bfe60f612a3c29955a">shark::benchmarks::LZ4</a></li>
<li>LZ5()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z5.html#a50b43aeb4b3cba2aa3ebdbc04bac2a33">shark::benchmarks::LZ5</a></li>
<li>LZ6()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z6.html#a5fbcd192f2aec7c1c0dd115b35baa22d">shark::benchmarks::LZ6</a></li>
<li>LZ7()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z7.html#affc4c175980ef9dbb11a39937a12df9c">shark::benchmarks::LZ7</a></li>
<li>LZ8()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z8.html#a661d5f639557c1a92b5413baab0604a3">shark::benchmarks::LZ8</a></li>
<li>LZ9()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_l_z9.html#a8cd552de8e1092c3c746e5eaa1a0506e">shark::benchmarks::LZ9</a></li>
</ul>
</div><!-- contents -->
</div>
</body>
</html>
